Rate My Professor Sarah Booth

Dr Sarah Booth is a Lecturer in Medical Statistics in the Biostatistics Research Group within the Department of Population Health Sciences at the University of Leicester. She obtained her PhD from the University of Leicester in 2021, with a thesis titled "Up-to-date prognostic modelling of more detailed population-based cancer data." Her research specializations and academic interests center on survival analysis and competing risks, methodology for developing, validating, and updating prognostic models, and analysis of population-based cancer registry data. Booth supervises postgraduate research students in biostatistics, focusing on these areas. She contributes to advancing statistical methods applicable to clinical prognosis in fields such as oncology and cardiology.

Booth's key publications demonstrate her impact in medical statistics. In 2020, she authored "Temporal recalibration for improving prognostic model calibration at new horizons," published in the International Journal of Epidemiology. This work introduced methods to adjust prognostic models for improving survival trends over time. In 2023, her paper "Using temporal recalibration to improve the calibration of risk prediction models when used in a new calendar time period" appeared in Statistics in Medicine. Recent contributions include "'Plugging the gap': development of a plain language glossary for statistical methodology research" in Research Involvement and Engagement (2025), aimed at enhancing patient and public involvement; "Calibration of cause-specific absolute risk for external validation using each cause-specific hazards model in the presence of competing events" (2025); "Association of symptoms at heart failure diagnosis with hospitalisation and mortality at 6 and 12 months: a retrospective cohort study using UK primary care health records" (2024); and "Using the kidney failure risk equation to predict end-stage kidney disease in CKD patients of South Asian ethnicity: an external validation study" (2023). She has collaborated on projects funded by Cancer Research UK and participates in NIHR initiatives. Her work influences prognostic modelling practices in population health research.